Taking the Intentional Stance Seriously, or "Intending" to Improve Cognitive Systems
This addresses the frustration in human-AI interactions for users by aiming to align systems with folk-psychological theories, though it is incremental as it builds on existing concepts.
The paper tackles the mismatch between human expectations and cognitive systems' limitations by proposing to imbue systems with mental states like intention, offering methodological suggestions for progress.
Finding claims that researchers have made considerable progress in artificial intelligence over the last several decades is easy. However, our everyday interactions with cognitive systems (e.g., Siri, Alexa, DALL-E) quickly move from intriguing to frustrating. One cause of those frustrations rests in a mismatch between the expectations we have due to our inherent, folk-psychological theories and the real limitations we experience with existing computer programs. The software does not understand that people have goals, beliefs about how to achieve those goals, and intentions to act accordingly. One way to align cognitive systems with our expectations is to imbue them with mental states that mirror those we use to predict and explain human behavior. This paper discusses these concerns and illustrates the challenge of following this route by analyzing the mental state 'intention.' That analysis is joined with high-level methodological suggestions that support progress in this endeavor.